Normal mode analysis as a method to derive protein dynamics information from the Protein Data Bank

Abstract

Normal mode analysis (NMA) can facilitate quick and systematic investigation of protein dynamics using data from the Protein Data Bank (PDB). We developed an elastic network model-based NMA program using dihedral angles as independent variables. Compared to the NMA programs that use Cartesian coordinates as independent variables, key attributes of the proposed program are as follows: (1) chain connectivity related to the folding pattern of a polypeptide chain is naturally embedded in the model; (2) the full-atom system is acceptable, and owing to a considerably smaller number of independent variables, the PDB data can be used without further manipulation; (3) the number of variables can be easily reduced by some of the rotatable dihedral angles; (4) the PDB data for any molecule besides proteins can be considered without coarse-graining; and (5) individual motions of constituent subunits and ligand molecules can be easily decomposed into external and internal motions to examine their mutual and intrinsic motions. Its performance is illustrated with an example of a DNA-binding allosteric protein, a catabolite activator protein. In particular, the focus is on the conformational change upon cAMP and DNA binding, and on the communication between their binding sites remotely located from each other. In this illustration, NMA creates a vivid picture of the protein dynamics at various levels of the structures, i.e., atoms, residues, secondary structures, domains, subunits, and the complete system, including DNA and cAMP. Comparative studies of the specific protein in different states, e.g., apo-and holo-conformations, and free and complexed configurations, provide useful information for studying structurally and functionally important aspects of the protein.

Long-range correlation in protein dynamics: Confirmation by structural data and normal mode analysis

“…Such a result indicates that the long-range correlations are encoded in the native topology of the proteins. Secondly, we conduct normal mode analysis [31][32][33] for protein molecules, ideal polymer chains, and lattice systems. A similar scaling relation holds for polymers, lattices, and proteins, but the scaling coefficients are different.…”

Slow Normal Modes of Proteins are Accurately Reproduced across Different Platforms

“…Since 2003, protein data bank Japan (PDBj.org), a worldwide protein data bank (ww-PDB) partner, provides ProMode elastic modal analyses of a large and growing number of PDB entries [26,27,39]. Initially configured to minimize coordinates to a nearby minimum of the potential energy surface, the current implementation of ProMode employs a GNMbased PDB-NMA [30] with the NCI spring constants between atoms i and j scaled according…”

Geometrical Conversion of the EGFR Extracellular Domain by Adiabatic Mapping Combining Normal Mode Analysis of the Elastic Network Model and Energy Optimization

“…To resolve this issue, we adopt NMA using the elastic network model (ENM-NMA), where the potential functions are solely harmonic terms with equilibrium positions residing on the studied structure. [24][25][26][27][28][29][30][31][32][33][34][35][36] This method does not require energy optimization and is appropriate to describe only low frequency normal modes that express collective motion such as interdomain motion. In this study, we comprehensively compare the X-ray crystal structures of ECD taken from The Protein Data Bank (PDB), 37) and discuss the process of ECD conversion by adiabatic mapping between the tethered and the extended forms.…”